Electric vehicle (EV) type choice model: Latent class modelling approach

This study develops a flexible Latent Class Model (LCM) to investigate the electric vehicle (EV) type choice decisions of Halifax residents. It utilizes cross-sectional data from the 2022 Halifax Travel Activity (HaliTRAC) survey, which includes questions related to EV adoption. This study also analyzes eight attitude and lifestyle preference related statements using principal component analysis (PCA) technique and finally extracts three components labeled as “EV enthusiasts”, “Sustainable travellers”, and “Remote work arrangement admirers”. This paper explores the heterogeneity between two classes for different alternative vehicle type choice, such as, battery electric vehicle (BEV), plug-in hybrid electric vehicle (PHEV), hybrid electric vehicle (HEV), and regular internal combustion engine (ICE) vehicle. Based on class membership attributes, class-1 can be identified as those who live in suburban areas, have a large family with high vehicle ownership, and are interested in travelling with their family members, especially with their children and vice-versa for class-2. Results suggest that variables across two classes portray heterogeneity, such as, full-time worker portray positive correlation for class-1 and negative to class-2; high annual household income group (more than $200,000) exhibit high propensity to choose BEV in class-2 and vice-versa for class-1. Sustainable travelers emphasize the adverse connection towards regular vehicles, while EV enthusiasts demonstrate a favorable association with embracing any type of EV (BEV, PHEV, HEV). Furthermore, the findings from this analysis provide guidance for policy measures such as offering purchase incentives, expanding charging infrastructure, and implementing tax rebates to promote the uptake of EV among the residents of Halifax.

Authors

Institutions

Publication Details

Journal
International Journal of Transportation Science and Technology
Published
2024-08-23
DOI
https://doi.org/10.1016/j.ijtst.2024.08.004
Citations
6
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
1.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Electric vehicle (EV) type choice model: Latent class modelling approach

Muhammad Ahsanul Habib, Hasan Shahrier
6 citations
International Journal of Transportation Science and Technology
Electric Vehicles and Infrastructure
1.25
article

Electric vehicle (EV) type choice model: Latent class modelling approach

Muhammad Ahsanul Habib, Hasan Shahrier
article en
6 citations

Abstract

This study develops a flexible Latent Class Model (LCM) to investigate the electric vehicle (EV) type choice decisions of Halifax residents. It utilizes cross-sectional data from the 2022 Halifax Travel Activity (HaliTRAC) survey, which includes questions related to EV adoption. This study also analyzes eight attitude and lifestyle preference related statements using principal component analysis (PCA) technique and finally extracts three components labeled as “EV enthusiasts”, “Sustainable travellers”, and “Remote work arrangement admirers”. This paper explores the heterogeneity between two classes for different alternative vehicle type choice, such as, battery electric vehicle (BEV), plug-in hybrid electric vehicle (PHEV), hybrid electric vehicle (HEV), and regular internal combustion engine (ICE) vehicle. Based on class membership attributes, class-1 can be identified as those who live in suburban areas, have a large family with high vehicle ownership, and are interested in travelling with their family members, especially with their children and vice-versa for class-2. Results suggest that variables across two classes portray heterogeneity, such as, full-time worker portray positive correlation for class-1 and negative to class-2; high annual household income group (more than $200,000) exhibit high propensity to choose BEV in class-2 and vice-versa for class-1. Sustainable travelers emphasize the adverse connection towards regular vehicles, while EV enthusiasts demonstrate a favorable association with embracing any type of EV (BEV, PHEV, HEV). Furthermore, the findings from this analysis provide guidance for policy measures such as offering purchase incentives, expanding charging infrastructure, and implementing tax rebates to promote the uptake of EV among the residents of Halifax.

International Journal of Transportation Science and TechnologyVol. 18
Dalhousie University (CA)
Affordable and clean energy
Openalex Percentile: Top 20%
Electric Vehicles and Infrastructure
1.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Electric vehicle (EV) type choice model: Latent class modelling approach — Muhammad Ahsanul Habib, Hasan Shahrier · International Journal of Transportation Science and Technology (2024) | TGRS Research Map | TGRS